The purpose of the proposed project is to develop and test error correction techniques for evaluating outcomes of community-based universal prevention programs. The specific over-arching goal is to develop analytical techniques for improved estimation of program effectiveness in community settings. We propose, first, to develop an analytic approach to address multiple sources of bias in the testing of program effectiveness. Second, we will apply this novel approach to the analysis of data from an ongoing program implementation. Third, we will estimate the degree to which the three sources of error affect estimates of how individual characteristics impact program outcomes. The proposed project is innovative in its combining of existing error correction techniques to adjust for multiple sources of bias simultaneously. It is significant in that it will result in improved estimation of program effectiveness through the integration of individual-level with aggregate-level analytic techniques. In turn, improved estimation of program effectiveness will provide policy makers and managers the information needed to understand population-level program impact;to calculate program benefits more accurately;to compare different implementations of the same program;and to refine programming and recruitment strategies. PUBLIC HEALTH RELEVANCE: The proposed project will provide new methods of estimating program benefits with greater accuracy. This will enable researchers to calculate whether the benefits of community-based prevention programs out weight their financial costs. Such knowledge is helpful to policy makers as they decide how to prioritize limited resources for social programs.